Send Postgres changes anywhere
Bring your own (or any) Postgres database
Never miss an insert, update, or delete
Automatic retries with replays
Simple HTTP interface
Key features
Key features
Key features
Give Postgres streaming powers
Give Postgres streaming powers
Sequin sends Postgres changes to your application and services. It’s designed to never miss an insert, update, or delete and provide exactly-once processing of changes. Your data stays in your database - no need to copy data to a new system or master a new technology.
How it works
How it works
How it works
Setup in minutes
Sequin comes with a web console for configuration. You'll read messages using an HTTP interface. You can GET messages (similar to SQS), or Sequin can POST messages to your app (webhooks).
Sequin comes with a web console for configuration. You'll read messages using an HTTP interface. You can GET messages (similar to SQS), or Sequin can POST messages to your app (webhooks).
Pull messages
Similar to SQS, you can GET messages from the stream and then ACK them.
Pull messages
Similar to SQS, you can GET messages from the stream and then ACK them.
Push messages
Push messages
Console
Console
Infra as code
Infra as code
curl -X 'GET' 'https://api.sequinstream.com/http_pull_consumers/pull/receive?batch_size=1'
# Returns
{
"record": {
"id": 159263,
"product": "H-100",
"quantity": 100,
"price": 3000000
},
"metadata": {
"table_schema": "public",
"table_name": "orders",
"commit_timestamp": "2024-08-22"
},
"action": "insert",
"changes": null,
"ack_id": "b93cfc27-4884-436c-b0c0-b87320c4dd53"
//Sequin pushes a payload to your HTTP endpoint
//Example lambda handler:
exports.order_handler = async (event) => {
try {
processOrder(event.action, event.record);
return {
//message will be ack'd
statusCode: 200,
};
} catch (error) {
console.error('Error:', error);
return {
//message will be nack'd & retried
statusCode: 500,
};
}
};resource "sequin_consumer" "h100_orders_consumer" {
name = "h100_orders"
source {
type = "postgres"
config = {
host = "aws.rds"
port = 5432
database = "postgres"
username = "postgres"
password = "▉▉▉▉"
ssl_mode = "disable"
}
}
table {
name = "orders"
schema = "public"
}
filter {
condition = "product = 'H-100'"
operation = "INSERT"
Pull messages
Similar to SQS, you can GET messages from the stream and then ACK them.
Pull messages
Similar to SQS, you can GET messages from the stream and then ACK them.
Push messages
Push messages
Console
Console
Infra as code
Infra as code
Pull messages
Similar to SQS, you can GET messages from the stream and then ack them.
Push messages
Console
Terraform
Use cases
Use cases
Use cases
Built to streamline
every use case
Built to streamline
every use case
Sequin allows you to turn the database you already know into the stream you need. It's designed to power the vast majority of streaming use cases. No need to master a new piece of infrastructure.
Benchmarks
Benchmarks
Benchmarks
Scales like Postgres
Sequin is built on the WAL to ensure no change is missed. If your database can handle the data, Sequin can stream it with minimal overhead.
Messages / Second
P95 Latency (MS)
Supported technologies
Supported technologies
Supported technologies
Works with your stack
Works
with your framework
Sequin offers a simple HTTP API, comes with a powerful console, and offers SDKs to help you implement Sequin quickly.
Sequin offers a simple HTTP API, comes with a powerful console, and offers SDKs to help you implement Sequin quickly.
Community
Community
Community
Open source
Open source
Sequin is completely open-source with an MIT license. Follow us on GitHub. Let us know what you want to see!
Sequin is completely open-source with an MIT license. Follow us on GitHub. Let us know what you want to see!
Keep it simple
Keep it simple
Postgres has evolved into a powerful database that can easily serve as the foundation of your stream. Boot Sequin, and experience a feature rich stream that is dead simple to run and scale.
Postgres has evolved into a powerful database that can easily serve as the foundation of your stream. Boot Sequin, and experience a feature rich stream that is dead simple to run and scale.
